Publications
Peer-reviewed journal articles
1. Hector EC, Song PXK (2020+). Doubly distributed supervised learning and inference with high-dimensional correlated outcomes. Accepted, Journal of Machine Learning Research.
2. Hector EC, Song PXK (2020). A distributed and integrated method of moments for high-dimensional correlated data analysis. Journal of the American Statistical Association, DOI: 10.1080/01621459.2020.1736082.
3. Perng W, Hector EC, Song PXK, Tellez Rojo MM, Raskind S, Kachman M, Cantoral A, Burant BF, Peterson KE. Metabolomic determinants of metabolic risk in Mexican adolescents. Obesity (Silver Spring) 2017. doi:10.1002/oby.21926
R packages
1. DIMM: Performs distributed and integrated method of moments regression for high- dimensional correlated responses. Divides outcomes into blocks, analyses blocks using composite likelihood, and combines estimators using a one-step update or an optimal generalized method of moments (GMM) equation.
2. DDIMM: Performs doubly distributed and integrated method of moments regression for high-dimensional correlated responses. Divides outcomes and subjects into blocks, analyses blocks using composite likelihood or generalized estimating equations, and combines estimators using a one-step update or an optimal GMM equation.
Peer-reviewed journal articles
1. Hector EC, Song PXK (2020+). Doubly distributed supervised learning and inference with high-dimensional correlated outcomes. Accepted, Journal of Machine Learning Research.
2. Hector EC, Song PXK (2020). A distributed and integrated method of moments for high-dimensional correlated data analysis. Journal of the American Statistical Association, DOI: 10.1080/01621459.2020.1736082.
3. Perng W, Hector EC, Song PXK, Tellez Rojo MM, Raskind S, Kachman M, Cantoral A, Burant BF, Peterson KE. Metabolomic determinants of metabolic risk in Mexican adolescents. Obesity (Silver Spring) 2017. doi:10.1002/oby.21926
R packages
1. DIMM: Performs distributed and integrated method of moments regression for high- dimensional correlated responses. Divides outcomes into blocks, analyses blocks using composite likelihood, and combines estimators using a one-step update or an optimal generalized method of moments (GMM) equation.
2. DDIMM: Performs doubly distributed and integrated method of moments regression for high-dimensional correlated responses. Divides outcomes and subjects into blocks, analyses blocks using composite likelihood or generalized estimating equations, and combines estimators using a one-step update or an optimal GMM equation.
